Business Understanding

Do data analysis on games data set so as to understand the relationship between the columns and predict the future values.

Data

This data was gotten from this site:

Visual Exploratory Descriptive Analysis

Import packages

Those are packages that are in the tidymodels which we are going to use in this project.

Import dataset

Rows: 1,512
Columns: 14
$ X_1               <dbl> 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, …
$ Title             <chr> "Elden Ring", "Hades", "The Legend of Zelda: Breath of the Wild", "Undertale", "Hollow Knight", "Minecraft", "Omori", "Metroid Dread", "Among Us", "NieR: Automata", "Persona 5 Royal", "Stray", "God of War", "Portal 2", "Bl…
$ Release_Date      <chr> "Feb 25, 2022", "Dec 10, 2019", "Mar 03, 2017", "Sep 15, 2015", "Feb 24, 2017", "Nov 18, 2011", "Dec 25, 2020", "Oct 07, 2021", "Jun 15, 2018", "Feb 23, 2017", "Oct 31, 2019", "Jul 19, 2022", "Apr 20, 2018", "Apr 18, 2011"…
$ Team              <chr> "['Bandai Namco Entertainment', 'FromSoftware']", "['Supergiant Games']", "['Nintendo', 'Nintendo EPD Production Group No. 3']", "['tobyfox', '8-4']", "['Team Cherry']", "['Mojang Studios']", "['OMOCAT', 'PLAYISM']", "['Ni…
$ Rating            <dbl> 4.5, 4.3, 4.4, 4.2, 4.4, 4.3, 4.2, 4.3, 3.0, 4.3, 4.4, 3.7, 4.2, 4.4, 4.5, 4.2, 4.4, 4.4, 4.1, 4.2, 3.7, 4.3, 4.1, 3.8, 3.3, 4.4, 4.4, 4.2, 4.6, 4.1, 4.2, 4.2, 4.1, 4.1, 4.1, 4.4, 4.2, 4.2, 2.6, 4.2, 3.9, 4.3, 4.3, 4.6, 4.…
$ Times_Listed      <chr> "3.9K", "2.9K", "4.3K", "3.5K", "3K", "2.3K", "1.6K", "2.1K", "867", "2.9K", "2.7K", "1.5K", "2.9K", "2.9K", "3.4K", "2.8K", "2.7K", "2.9K", "2K", "2.9K", "1.6K", "926", "2.1K", "2.1K", "1.5K", "1.7K", "1.4K", "1.6K", "1.1…
$ Number_of_Reviews <chr> "3.9K", "2.9K", "4.3K", "3.5K", "3K", "2.3K", "1.6K", "2.1K", "867", "2.9K", "2.7K", "1.5K", "2.9K", "2.9K", "3.4K", "2.8K", "2.7K", "2.9K", "2K", "2.9K", "1.6K", "926", "2.1K", "2.1K", "1.5K", "1.7K", "1.4K", "1.6K", "1.1…
$ Genres            <chr> "['Adventure', 'RPG']", "['Adventure', 'Brawler', 'Indie', 'RPG']", "['Adventure', 'RPG']", "['Adventure', 'Indie', 'RPG', 'Turn Based Strategy']", "['Adventure', 'Indie', 'Platform']", "['Adventure', 'Simulator']", "['Adv…
$ Summary           <chr> "Elden Ring is a fantasy, action and open world game with RPG elements such as stats, weapons and spells. Rise, Tarnished, and be guided by grace to brandish the power of the Elden Ring and become an Elden Lord in the Land…
$ Reviews           <chr> "[\"The first playthrough of elden ring is one of the best eperiences gaming can offer you but after youve explored everything in the open world and you've experienced all of the surprises you lose motivation to go explori…
$ Plays             <chr> "17K", "21K", "30K", "28K", "21K", "33K", "7.2K", "9.2K", "25K", "18K", "12K", "7.7K", "21K", "29K", "17K", "20K", "15K", "19K", "28K", "25K", "9.1K", "3K", "14K", "30K", "13K", "5.3K", "3.9K", "5.9K", "6K", "21K", "19K", …
$ Playing           <chr> "3.8K", "3.2K", "2.5K", "679", "2.4K", "1.8K", "1.1K", "759", "470", "1.1K", "2.3K", "801", "1.1K", "471", "1.1K", "1.2K", "1.8K", "1.7K", "244", "710", "1.6K", "866", "492", "829", "1.5K", "801", "795", "955", "1.2K", "57…
$ Backlogs          <chr> "4.6K", "6.3K", "5K", "4.9K", "8.3K", "1.1K", "4.5K", "3.4K", "776", "6.2K", "5.1K", "2.5K", "4.8K", "3.9K", "5.6K", "5.9K", "6.4K", "5.5K", "2.7K", "2.9K", "2.5K", "1.5K", "4.2K", "3.2K", "4.7K", "2K", "2.1K", "2.5K", "5K…
$ Wishlist          <chr> "4.8K", "3.6K", "2.6K", "1.8K", "2.3K", "230", "3.8K", "3.3K", "126", "3.6K", "3K", "3.4K", "2.6K", "1.2K", "3.3K", "2K", "2K", "2.9K", "1.1K", "2K", "2.1K", "2K", "2K", "664", "2.9K", "3.3K", "2.2K", "3.1K", "2.7K", "2.2K…

Our data set has 1,512 and 14 columns

Explore the data class structure visually

Most of the coulmns in our data set are character data type.

convert all remaining character variables to factors

There is no character data type column.

Visualizing missing data

Viewing missing dataset

              X_1             Title      Release_Date              Team            Rating      Times_Listed Number_of_Reviews            Genres           Summary           Reviews             Plays           Playing          Backlogs 
                0                 0                 0                 1                13                 0                 0                 0                 1                 0                 0                 0                 0 
         Wishlist 
                0 

The only coulmns with missing data are Team,Rating and Summary.

Fill missing data with mode

              X_1             Title      Release_Date              Team            Rating      Times_Listed Number_of_Reviews            Genres           Summary           Reviews             Plays           Playing          Backlogs 
                0                 0                 0                 1                13                 0                 0                 0                 1                 0                 0                 0                 0 
         Wishlist 
                0 

Now there is no missing data.

1.Bubble chart of game ratings and number of reviews

Error in `geom_point()`:
! Problem while computing aesthetics.
ℹ Error occurred in the 1st layer.
Caused by error:
! object 'Number of Reviews' not found

Most games had a review of 4 and relatively they were around 500.

Box plot of game ratings

There are many outliers in the boxplot of game ratings.

Scatter plot of number of reviews vs. rating

Histogram of game ratings

The game ratings has normal distribution.

Bar chart of game ratings

## Non-Visual Exploratory Data Analysis

Top rows of our data set

Bottom rows of our data set

From the two tables we can say our data is not biased. ## Structure of our data set

Rows: 1,512
Columns: 14
$ X_1               <dbl> 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, …
$ Title             <fct> "Elden Ring", "Hades", "The Legend of Zelda: Breath of the Wild", "Undertale", "Hollow Knight", "Minecraft", "Omori", "Metroid Dread", "Among Us", "NieR: Automata", "Persona 5 Royal", "Stray", "God of War", "Portal 2", "Bl…
$ Release_Date      <fct> "Feb 25, 2022", "Dec 10, 2019", "Mar 03, 2017", "Sep 15, 2015", "Feb 24, 2017", "Nov 18, 2011", "Dec 25, 2020", "Oct 07, 2021", "Jun 15, 2018", "Feb 23, 2017", "Oct 31, 2019", "Jul 19, 2022", "Apr 20, 2018", "Apr 18, 2011"…
$ Team              <fct> "['Bandai Namco Entertainment', 'FromSoftware']", "['Supergiant Games']", "['Nintendo', 'Nintendo EPD Production Group No. 3']", "['tobyfox', '8-4']", "['Team Cherry']", "['Mojang Studios']", "['OMOCAT', 'PLAYISM']", "['Ni…
$ Rating            <dbl> 4.5, 4.3, 4.4, 4.2, 4.4, 4.3, 4.2, 4.3, 3.0, 4.3, 4.4, 3.7, 4.2, 4.4, 4.5, 4.2, 4.4, 4.4, 4.1, 4.2, 3.7, 4.3, 4.1, 3.8, 3.3, 4.4, 4.4, 4.2, 4.6, 4.1, 4.2, 4.2, 4.1, 4.1, 4.1, 4.4, 4.2, 4.2, 2.6, 4.2, 3.9, 4.3, 4.3, 4.6, 4.…
$ Times_Listed      <fct> 3.9K, 2.9K, 4.3K, 3.5K, 3K, 2.3K, 1.6K, 2.1K, 867, 2.9K, 2.7K, 1.5K, 2.9K, 2.9K, 3.4K, 2.8K, 2.7K, 2.9K, 2K, 2.9K, 1.6K, 926, 2.1K, 2.1K, 1.5K, 1.7K, 1.4K, 1.6K, 1.1K, 2.5K, 2.4K, 1.5K, 2.6K, 2.5K, 1.9K, 2.3K, 2.9K, 1.9K, …
$ Number_of_Reviews <fct> 3.9K, 2.9K, 4.3K, 3.5K, 3K, 2.3K, 1.6K, 2.1K, 867, 2.9K, 2.7K, 1.5K, 2.9K, 2.9K, 3.4K, 2.8K, 2.7K, 2.9K, 2K, 2.9K, 1.6K, 926, 2.1K, 2.1K, 1.5K, 1.7K, 1.4K, 1.6K, 1.1K, 2.5K, 2.4K, 1.5K, 2.6K, 2.5K, 1.9K, 2.3K, 2.9K, 1.9K, …
$ Genres            <fct> "['Adventure', 'RPG']", "['Adventure', 'Brawler', 'Indie', 'RPG']", "['Adventure', 'RPG']", "['Adventure', 'Indie', 'RPG', 'Turn Based Strategy']", "['Adventure', 'Indie', 'Platform']", "['Adventure', 'Simulator']", "['Adv…
$ Summary           <fct> "Elden Ring is a fantasy, action and open world game with RPG elements such as stats, weapons and spells. Rise, Tarnished, and be guided by grace to brandish the power of the Elden Ring and become an Elden Lord in the Land…
$ Reviews           <fct> "[\"The first playthrough of elden ring is one of the best eperiences gaming can offer you but after youve explored everything in the open world and you've experienced all of the surprises you lose motivation to go explori…
$ Plays             <fct> 17K, 21K, 30K, 28K, 21K, 33K, 7.2K, 9.2K, 25K, 18K, 12K, 7.7K, 21K, 29K, 17K, 20K, 15K, 19K, 28K, 25K, 9.1K, 3K, 14K, 30K, 13K, 5.3K, 3.9K, 5.9K, 6K, 21K, 19K, 6.7K, 21K, 25K, 18K, 14K, 15K, 13K, 14K, 2.2K, 9.9K, 21K, 16K,…
$ Playing           <fct> 3.8K, 3.2K, 2.5K, 679, 2.4K, 1.8K, 1.1K, 759, 470, 1.1K, 2.3K, 801, 1.1K, 471, 1.1K, 1.2K, 1.8K, 1.7K, 244, 710, 1.6K, 866, 492, 829, 1.5K, 801, 795, 955, 1.2K, 577, 851, 880, 463, 1.2K, 1.2K, 919, 1.1K, 1.5K, 2.7K, 419, 3…
$ Backlogs          <fct> 4.6K, 6.3K, 5K, 4.9K, 8.3K, 1.1K, 4.5K, 3.4K, 776, 6.2K, 5.1K, 2.5K, 4.8K, 3.9K, 5.6K, 5.9K, 6.4K, 5.5K, 2.7K, 2.9K, 2.5K, 1.5K, 4.2K, 3.2K, 4.7K, 2K, 2.1K, 2.5K, 5K, 2.9K, 4.3K, 4.1K, 2.5K, 1.1K, 4.5K, 4.8K, 5K, 5.2K, 1.3…
$ Wishlist          <fct> 4.8K, 3.6K, 2.6K, 1.8K, 2.3K, 230, 3.8K, 3.3K, 126, 3.6K, 3K, 3.4K, 2.6K, 1.2K, 3.3K, 2K, 2K, 2.9K, 1.1K, 2K, 2.1K, 2K, 2K, 664, 2.9K, 3.3K, 2.2K, 3.1K, 2.7K, 2.2K, 2.2K, 3.7K, 775, 801, 2.6K, 3.4K, 1.5K, 2.2K, 280, 2.2K, …

Our data set has just numeric and factor data type columns as data cleaning. ## Statistical summary of our data set

Data summary

Name	data
Number of rows	1512
Number of columns	14
_______________________
Column type frequency:
factor	12
numeric	2
________________________
Group variables	None

Variable type: factor

skim_variable	n_missing	complete_rate	ordered	n_unique	top_counts
Title	0	1	FALSE	1099	Doo: 7, Dea: 5, Res: 5, Sha: 5
Release_Date	0	1	FALSE	987	Nov: 8, Nov: 7, Jun: 6, Jun: 5
Team	1	1	FALSE	764	[’C: 35, [’S: 31, [’N: 19, [’N: 19
Times_Listed	0	1	FALSE	606	1.1: 46, 1.2: 39, 1.3: 34, 1.5: 27
Number_of_Reviews	0	1	FALSE	606	1.1: 46, 1.2: 39, 1.3: 34, 1.5: 27
Genres	0	1	FALSE	255	[’A: 154, [’A: 107, [’A: 82, [’S: 72
Summary	1	1	FALSE	1112	Min: 4, ’Da: 3, A 2: 3, A 3: 3
Reviews	0	1	FALSE	1117	[]: 12, [’A: 3, [’A: 3, [’A: 3
Plays	0	1	FALSE	258	12K: 50, 13K: 40, 14K: 39, 1.6: 33
Playing	0	1	FALSE	396	1.1: 24, 1.2: 17, 22: 14, 2: 13
Backlogs	0	1	FALSE	544	1.5: 52, 1.1: 43, 1.3: 42, 1.8: 33
Wishlist	0	1	FALSE	573	1.3: 41, 1.2: 39, 1.1: 30, 1.4: 30

Variable type: numeric

skim_variable	n_missing	complete_rate	mean	sd	p0	p25	p50	p75	p100	hist
X_1	0	1.00	755.50	436.62	0.0	377.75	755.5	1133.25	1511.0	▇▇▇▇▇
Rating	13	0.99	3.72	0.53	0.7	3.40	3.8	4.10	4.8	▁▁▂▇▆

Create a new data frame that contains only the games that have been played at least 10,000 times

Create a new data frame that contains only the games with a rating of 4 or higher

These are games with rating of 4 and above.

Data wrangling

Here are some data wrangling done in the above: * Filling missing data with mode. * Convert all character columns to factor.

Convert columns with numeric values to numeric type

Error in `mutate()`:
ℹ In argument: `across(...)`.
Caused by error in `across()`:
! Can't subset columns that don't exist.
✖ Column `Times Listed` doesn't exist.

Convert ‘Release Date’ column to Date type

Error in `$<-.data.frame`(`*tmp*`, `Release Date`, value = structure(numeric(0), class = "Date")): replacement has 0 rows, data has 1512

Extract year and month from ‘Release Date’

Error in `$<-.data.frame`(`*tmp*`, Year, value = numeric(0)): replacement has 0 rows, data has 1512

Error in `$<-.data.frame`(`*tmp*`, Month, value = structure(integer(0), levels = c("Jan", : replacement has 0 rows, data has 1512

Split ‘Genres’ column into separate genre columns

Remove unnecessary columns

Error in `select()`:
! Can't subset columns that don't exist.
✖ Column `...1` doesn't exist.

Rename columns to remove spaces and special characters

Convert K values to numeric in columns with “K” suffix

Error in `[.data.frame`(data_filled, , c("Times.Listed", "Number.of.Reviews", : undefined columns selected

Create a new column called Total Plays that is the sum of the Plays and Playing columns

[1] NA NA NA NA NA NA

Create a new column called Average Rating that is the average of the Rating column.

Group the data by Genre and calculate the total number of games in each genre

See the data after data wrangling

Rows: 1,512
Columns: 16
$ X_1               <dbl> 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, …
$ Title             <int> 252, 377, 973, 1041, 404, 588, 644, 575, 19, 628, 677, 878, 353, 724, 84, 131, 1083, 751, 723, 902, 705, 396, 559, 364, 168, 356, 1078, 460, 214, 528, 176, 627, 894, 915, 166, 796, 291, 675, 344, 822, 764, 899, 270, 648, 7…
$ Release_Date      <int> 281, 166, 482, 919, 278, 703, 205, 769, 441, 275, 871, 384, 33, 23, 551, 330, 507, 839, 776, 846, 341, 332, 261, 926, 162, 655, 411, 556, 572, 892, 552, 38, 458, 156, 980, 542, 348, 440, 976, 848, 581, 625, 811, 617, 331, …
$ Team              <int> 78, 650, 449, 690, 659, 378, 494, 440, 297, 509, 71, 116, 603, 723, 244, 224, 552, 656, 723, 464, 430, 657, 329, 543, 142, 603, 383, 276, 761, 300, 78, 696, 443, 605, 642, 239, 616, 478, 372, 549, 133, 466, 489, 376, 121, …
$ Rating            <dbl> 4.5, 4.3, 4.4, 4.2, 4.4, 4.3, 4.2, 4.3, 3.0, 4.3, 4.4, 3.7, 4.2, 4.4, 4.5, 4.2, 4.4, 4.4, 4.1, 4.2, 3.7, 4.3, 4.1, 3.8, 3.3, 4.4, 4.4, 4.2, 4.6, 4.1, 4.2, 4.2, 4.1, 4.1, 4.1, 4.4, 4.2, 4.2, 2.6, 4.2, 3.9, 4.3, 4.3, 4.6, 4.…
$ Times_Listed      <int> 185, 100, 270, 184, 269, 94, 7, 92, 556, 100, 98, 6, 100, 100, 183, 99, 98, 100, 182, 100, 7, 582, 92, 92, 6, 8, 5, 7, 2, 96, 95, 6, 97, 96, 10, 94, 100, 10, 451, 533, 9, 98, 182, 9, 96, 9, 2, 8, 8, 96, 93, 182, 9, 10, 8, …
$ Number_of_Reviews <int> 185, 100, 270, 184, 269, 94, 7, 92, 556, 100, 98, 6, 100, 100, 183, 99, 98, 100, 182, 100, 7, 582, 92, 92, 6, 8, 5, 7, 2, 96, 95, 6, 97, 96, 10, 94, 100, 10, 451, 533, 9, 98, 182, 9, 96, 9, 2, 8, 8, 96, 93, 182, 9, 10, 8, …
$ Genres            <int> 126, 22, 126, 70, 56, 132, 70, 92, 207, 166, 125, 80, 34, 83, 126, 56, 32, 116, 215, 92, 125, 24, 35, 129, 116, 38, 126, 92, 72, 38, 126, 126, 92, 180, 148, 38, 125, 119, 126, 80, 129, 92, 231, 66, 129, 246, 125, 167, 199,…
$ Summary           <int> 294, 57, 920, 69, 20, 599, 83, 508, 513, 624, 110, 555, 401, 761, 105, 422, 898, 718, 1056, 330, 952, 133, 252, 408, 234, 402, 86, 509, 261, 822, 237, 623, 887, 541, 233, 303, 351, 108, 393, 781, 733, 23, 481, 646, 721, 25…
$ Reviews           <int> 1056, 141, 705, 627, 1079, 445, 1053, 253, 956, 263, 758, 543, 214, 714, 887, 765, 716, 517, 161, 816, 673, 373, 704, 522, 952, 61, 1011, 404, 810, 528, 679, 478, 769, 577, 202, 948, 270, 441, 958, 611, 706, 693, 1058, 591…
$ Plays             <int> 30, 55, 90, 73, 55, 96, 184, 235, 66, 35, 18, 189, 55, 76, 30, 52, 24, 39, 73, 66, 234, 107, 23, 90, 21, 136, 87, 142, 182, 55, 39, 166, 55, 66, 35, 23, 24, 21, 23, 43, 242, 55, 29, 189, 24, 35, 108, 21, 52, 21, 217, 30, 2…
$ Playing           <int> 180, 179, 106, 329, 105, 8, 3, 350, 266, 3, 104, 361, 3, 267, 3, 4, 8, 7, 141, 338, 6, 372, 275, 364, 5, 361, 358, 391, 4, 300, 370, 377, 261, 4, 4, 383, 3, 5, 107, 242, 205, 263, 349, 325, 304, 290, 102, 314, 177, 268, 16…
$ Backlogs          <int> 219, 360, 356, 222, 464, 2, 218, 148, 456, 359, 293, 75, 221, 152, 296, 297, 361, 295, 77, 79, 75, 6, 216, 146, 220, 144, 71, 75, 356, 79, 217, 215, 75, 2, 218, 221, 356, 294, 4, 10, 78, 145, 356, 221, 150, 291, 148, 356, …
$ Wishlist          <int> 267, 192, 105, 8, 102, 132, 194, 190, 34, 192, 265, 191, 105, 2, 190, 187, 187, 108, 1, 187, 100, 187, 187, 434, 108, 190, 101, 189, 106, 101, 101, 193, 488, 501, 105, 191, 5, 101, 173, 101, 107, 2, 4, 189, 9, 4, 105, 102,…
$ `Total Plays`     <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
$ Average_Rating    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…

That is our new data frame after data wrangling.

Visual analysis(Time series analysis using ARIMA model)

Convert the data to a time series

Fit an ARIMA model

Forecast future values

Visualize the time series and forecast

These data show random variation; There are no patterns or cycles.